Despite the growing growth of technology, handwritten signature has been selected as the first option between biometrics by users. In this paper, a new methodology for offline handwritten signature verification and recognition based on the Shearlet transform and transfer learning is proposed. Since, a large percentage of handwritten signatures are composed of curves and the performance of a sig...

the problem of automatic signature recognition has received little attention incomparison with the problem of signature verification, despite its potentialapplications for many business processes and can be used effectively in paperlessoffice projects. this paper presents model-based off-line signature recognition withrotation invariant features. non-linear rotation of signature patterns is one...

Signatures are one of the most important techniques for biometric authentication. There two kinds signature nowadays, offline(static) and dynamic (online). greater distinctive characteristics offline signatures, but there less signatures. Offline signatures also harder to check. Furthermore, significant downside is that even talented signer does not sign same way. This called Intra-personal var...

A number of biometric techniques have been used for personal identification such as face recognition, fingerprint recognition, voice recognition and signature recognition. However signature verification is most widely used. Signature being the most prominent handwritten proof of identity is used for authentication of documents in the fields of financial, commercial and legal transactions which ...

– The problem of automatic signature recognition has received little attention in comparison with the problem of signature verification despite its potential applications for accessing security-sensitive facilities and for processing certain legal and historical documents. This paper presents an efficient off-line human signature recognition system based on Support Vector Machines (SVM) and com...

In this paper we will evaluate the use of SURF features in handwritten signature verification. For each known writer we will take a sample of three genuine signatures and extract their SURF descriptors. In this paper, off-line signature recognition & verification using neural network is proposed, where the signature is captured and presented to the user in an image format. Signatures are verifi...